Embodiments of the invention are directed, in general, to communication systems and, more specifically, to sensor assisted GNSS receivers.
Any satellite-based navigation system suffers significant performance degradation when satellite signal is blocked, attenuated and/or reflected (multipath), for example, indoor and in urban canyons. As MEMS technologies advance, it becomes more interested to integrate sensor-based inertial navigation system (INS) solutions into global navigation satellite system (GNSS) receivers, in pedestrian applications as well as in vehicle applications.
As GNSS receivers become more common, users continue to expect improved performance in increasingly difficult scenarios. GNSS receivers may process signals from one or more satellites from one or more different satellite systems. Currently existing satellite systems include global positioning system (GPS), and the Russian global navigation satellite system (Russian: , abbreviation of tr.: GLObal'naya NAvigatsionnaya Sputnikovaya Sistema; “GLObal NAvigation Satellite System” (GLONASS). Systems expected to become operational in the near future include Galileo, quasi-zenith satellite system (QZSS), and the Chinese system Beidou. For many years, inertial navigation systems have been used in high-cost applications such as airplanes to aid GNSS receivers in difficult environments. One example that uses inertial sensors to allow improved carrier-phase tracking may be found in A. Soloviev, S. Gunawardena, and F. van Graas, “Deeply integrated GPS/Low-cost IMU for low CNR signal processing: concept description and in-flight demonstration,” Journal of the Institute of Navigation, vol. 55, No. 1, Spring 2008; incorporated herein by reference. The recent trend is to try to integrate a GNSS receiver with low-cost inertial sensors to improve performance when many or all satellite signals are severely attenuated or otherwise unavailable. The high-cost and low-cost applications for these inertial sensors are very different because of the quality and kinds of sensors that are available. The problem is to find ways that inexpensive or low-cost sensors can provide useful information to the GNSS receiver.
Low-cost sensors may not be able to provide full navigation data. Or they may only work in some scenarios. In the past, most integration techniques for GNSS receivers and sensors assumed the sensors constituted a complete stand-alone navigation system or that its expensive components allow it to give precise measurements. Low-cost sensors cannot always allow for these assumptions. In addition, traditionally the INS is assumed to be fully calibrated, which is not always possible.
What is needed is low-complexity GNSS/IMU integration apparatus and methods to improve GNSS performance in harsh environments such as indoors, parking garages, deep urban canyons, and the like.